We are implementing a up-to-date data and analytics platform to strengthen data quality, governance, automation, and insight generation across our insurance and broader enterprise reporting functions.
We operate in a regulated, high-sensitivity environment and are building sustainable internal capability to operate and extend our data solutions over time.
This is a hands-on technical role contributing directly to our Databricks platform implementation.
You will work alongside engineering, architecture, and data governance colleagues, collaborating across actuarial, IT, security, and implementation partners.
NB: **This position requires you to be an Australian Citizen living in Sydney** The Responsibilities Contribute to day-to-day technical delivery across actuarial, business, IT, and vendor stakeholders.
Build and maintain Databricks pipelines, notebooks, Unity Catalog configurations, orchestration workflows, and performance optimisations.
Support migration of priority data assets, processing logic, and analytics code into Databricks.
Develop reusable patterns that support maintainability, governance, auditability, and performance.
Apply governance practices: version control, code review, CI/CD, access control, data quality checks, and documentation standards.




Adhere to and contribute to standards for open source, libraries, and third-party components including security and licensing compliance.
Participate in technical reviews of key artefacts; support management of technical debt and BAU readiness.
Contribute to knowledge sharing and capability building to reduce reliance on external vendors.
The Requirements 7+ years hands-on data engineering experience delivering production-grade solutions end-to-end.
Solid Databricks / Spark delivery in production: pipeline build, orchestration, performance tuning, and operationalisation.
Exposure to data governance practices: RBAC, audit logging, lineage, data quality gates, and change control.
Experience working in a regulated or high-sensitivity data environment with strong security discipline.
Ability to collaborate effectively in co-delivery models with vendors and internal teams.
Strong SQL and Python (including PySpark); solid software engineering discipline including Git, PR/code review, and CI/CD.
Desirable Databricks Certified Data Engineer To be considered for this position, you must have real world working experience in Databricks – only those who have the same will be considered.

📌 Senior Data Engineer – Databricks (New South Wales)
🏢 Precision Sourcing
📍 New South Wales